Systems genomics approaches in neurologic disease

Abstract

Neurologic disorders encompass a broad range of diseases including neurodegenerative (Huntington's disease, Parkinson's disease, Alzheimer's), neurodevelopmental (Autism, Rett syndrome), and psychiatric or mental disorders (Schizophrenia, bipolar disorder). Changes in brain gene expression accompany many of these disorders as demonstrated in studies of human post-mortem tissue. A critical objective in our understanding of gene misregulation in neurologic diseases, which range in heritability, is a comprehensive characterization of the spatial and temporal dynamics of the associated changes and how gene regulatory drivers mediate them. In this work, I explore early gene expression changes in a longitudinal study of Huntington’s disease (HD) mouse models, and survey gene networks enriched for differential gene expression. I go on to investigate the contributions of sequence-specific transcription factors (TFs) to disease-specific gene expression change in HD and psychiatric disorders. I begin with a genome-scale model for TF-target gene interactions by combining publicly available DNase-seq footprinting and brain transcriptomic datasets. Using this transcriptional regulatory network (TRN), we identified TFs whose predicted target genes were overrepresented among differentially expressed genes in neurologic disorders. Following the identification of these predicted driver TFs, I applied multiple functional genomics approaches to characterize their genome-wide binding sites (ChIP-seq), survey the impact of TF overexpression or knockdown (overexpression or CRISPR-Cas9-mediated editing), and assess the functional consequences of variation present in a motif instance (luciferase reporter assay). Together the findings from these studies further our understanding of the functional networks of genes and TFs implicated in neurologic disease and provide a methodological framework for future applications beyond the diseases covered in this thesis.